LED Intensity Decay Particle Tracking Velocimetry (PTV)

The conventional approaches for measuring focused laser differential interferometry either use a single-point mechanism that cannot calculate velocity or a system that creates non-parallel beams in the testing zone, causing differences in time to travel between beams throughout the testing zone, adding a level of uncertainty to velocity measurements. For this technology, the inventors determined that the best approach is to use a method that ensures all laser beams propagating between the transmitter and receiver sides of the instrument are parallel to one another. This is done by crossing two orthogonally polarized beams at a Wollaston prism located just ahead of the field lens on the transmitter side of the FLDI. The polarization orientation of the two crossing beams must be at ±45 degrees to one another so that the Wollaston prism can further split the beams by a small angle (this gives the instrument its sensitivity to density fluctuations at each measurement point). The use of wedge prisms (that comprise the beam crossing system) to redirect the split beams such that they cross the optical axis minimizes any distortion imparted to the beams. This is in contrast to the use of a spherical focusing lens to redirect the split beams, which can impart undesirable distortions to the beams and affect the focusing properties of the FLDI instrument between its transmitter and receiver sides.

The Projected BOS imaging system developed at the NASA Langley Research Center provides a significant advancement over other BOS flow visualization techniques. Specifically, the present BOS imaging method removes the need for a physically patterned retroreflective background within the flow of interest and is therefore insensitive to the changing conditions due to the flow. For example, in a wind tunnel used for aerodynamics testing, there are vibrations and temperature changes that can affect the entire tunnel and anything inside it. Any patterned background within the wind tunnel will be subject to these changing conditions and those effects must be accounted for in the post-processing of the BOS image. This post-processing is not necessary in the Projected BOS process here. In the Projected BOS system, a pattern is projected onto a retroreflective background across the flow of interest (Figure 1). The imaged pattern in this configuration can be made physically (a pattern on a transparent slide) or can be digitally produced on an LCD screen. In this projection scheme, a reference image can be taken at the same time as the signal image, facilitating real-time BOS imaging and the pattern to be changed or optimized during the measurements. Thus far, the Projected BOS imaging technology has been proven to work by visualizing the air flow out of a compressed air canister taken with this new system (Figure 2).

The system combines laser goggles with an optical head-mounted display that displays a real-time video camera image of a laser beam. Users are able to visualize the laser beam while his/her eyes are protected. The system also allows for numerous additional features in the optical head mounted display such as digital zoom, overlays of additional information such as power meter data, Bluetooth wireless interface, digital overlays of beam location and others. The system is built on readily available components and can be used with existing laser eyewear. The software converts the color being observed to another color that transmits through the goggles. For example, if a red laser is being used and red-blocking glasses are worn, the software can convert red to blue, which is readily transmitted through the laser eyewear. Similarly, color video can be converted to black-and-white to transmit through the eyewear.

Blood circulation carries vibrations due to heart beat to every part of the body. These vibrations result in minute displacements that are measured by the detector. Defective closures lead to backflow of blood into chambers leading to heart beat slowdown. Displacement strength is indicative of vibration strength which in turn is indicative of heart beat. Weak vibrations at toes, for example, indicate poor circulation of blood as in the case of diabetic issues. Similarly, in other parts of the body, this unit would help in early detection of diabetes and other diseases by noninvasively monitoring blood circulation at various regions of a human body. As such, this unit would detect precursors for diseases. For astronauts and other operatives, this device could remotely provide the status of their cardiac cycles during physical activities. The device consists of a laser transmitter, photo-EMF detector and interferometric architecture which provides motion detection. Motion detection aids in measuring displacements. There is also a "speckle tolerant" property allowing data to be collected from conformal and rough target surfaces such as garments. Surface preparation is not needed such as in ECG and other cases. The novel Photo-EMF detector will be able to measure displacements of less than 1 pm.

The current Star Tracker software package is comprised of a Lumenera LW230 monochrome machine-vision camera and a FUJINON HF35SA-1 35mm lens. The star tracker cameras are all connected to and powered by the PC/104 stack via USB 2.0 ports. The software code is written in C++ and is can easily be adapted to other camera and lensing platforms by setting new variables in the software for new focal conditions. In order to identify stars in images, the software contains a star database derived from the 118,218-star Hipparcos catalog [1]. The database contains a list of every star pair within the camera field of view and the angular distance between those pairs. It also contains the inertial position information for each individual star directly from the Hipparcos catalog. In order to keep the star database size small, only stars of magnitude 6.5 or brighter were included. The star tracking process begins when image data is retrieved by the software from the data buffers in the camera. The image is translated into a binary image via a threshold brightness value so that on (bright) pixels are represented by 1s and off (dark) pixels are represented by 0s. The binary image is then searched for blobs, which are just connected groups of on pixels. These blobs represent unidentified stars or other objects such as planets, deep sky objects, other satellites, or noise. The centroids of the blob locations are computed, and a unique pattern recognition algorithm is applied to identify which, if any, stars are represented. During this process, false stars are effectively removed and only repeatedly and uniquely identifiable stars are stored. After stars are identified, another algorithm is applied on their position information to determine the attitude of the satellite. The attitude is computed as a set of Euler angles: right ascension (RA), declination (Dec), and roll. The first two Euler angles are computed by using a linear system that is derived from vector algebra and the information of two identified stars in the image. The roll angle is computed using an iterative method that relies on the information of a single star and the first two Euler angles. [1] ESA, 1997, The Hipparcos and Tycho Catalogues, ESA SP-1200